Remote sensing –Beyond images Mexico 14-15 December 2013 The workshop was organized by CIMMYT Global Conservation Agriculture Program (GCAP) and funded by the Bill & Melinda Gates Foundation (BMGF), the Mexican Secretariat of Agriculture, Livestock, Rural Development, Fisheries and Food (SAGARPA), the International Maize and Wheat Improvement Center (CIMMYT), CGIAR Research Program on Maize, the Cereal System Initiative for South Asia (CSISA) and the Sustainable Modernization of the Traditional Agriculture (MasAgro)

1. Agrometeorological stations
and weather and
climate forecasts
Arturo Corrales Suastegui
Miguel Angel Gonzalez Gonzalez
Mario P. Narváez Mendoza
December 15, 2013

2. Outline
• National Agrometeorological Network
• Climate Forecast
• Meteorological Forecast (WRF)
• References

3. National Agrometeorological Network
• Over 1,000 Agrometeorological stations in 29
states in Mexico
• Information stored every 15 minutes of
meteorological variables, such as:




Temperature
Precipitation
Wind speed and direction
Global radiation
• Data Collected in the Laboratorio Nacional
de Modelaje y Sensores Remotos (INIFAP)

4. National Agrometeorological Network

5. National Agrometeorological Network
Posting:
• Data in real time
 Internet Web site:
http://clima.inifap.gob.mx
• Processed Data
 Weather and climate maps
 Agrometeorological applications
(units heat, cold hours, etc.)
• Leaflets
• Android and IOS apps (1st demo)

6. Climate Forecast
Climate Model:
•
Statistical model
•
Canonical correlation analysis
•
Predictants (11 oceanicatmospheric variables)
Predictors (Monthly precipitation
and frost days)
•
640 weather stations (Monthly
historical number of days with
temperature <2 °C and Monthly
precipitation data, 1961-2008)

7. Climate Forecast
Climate Outlooks (Precipitation)
Montly Outlook (anomalies)
1
2
3

8. Climate Forecast
Climate Model – Hindcasts:
•
Point evaluation: same point
forecasted vs same point registered
•
Simulation of monthly historical
forecasts (1961-2008)
•
Historical and simulated montlhy data
transformed to terciles
•
Tercile simulated vs Tercile registered
by contingency table ( Hanssen
Kuipers Skill Score) for each weather
station

9. Climate Forecast
Climate Model - Hindcast for the Rainy Season in Mexico:
Forecast release
Outlook month
1
2
3
24 April 2013
0.60
0.45
0.39
24 May 2013
0.44
0.41
0.44
24 Jun 2013
0.41
0.46
0.54
24 July 2013
0.46
0.65
0.51
23 August 2013
0.58
0.57
24 September 2013
0.62
Mean
0.48
Overall Hanssen-Kuipers Skill Score
0.49
0.47
0.48

10. Meteorological Forecast
WRF model (1 to 5 days forecasts):
•
January 2012:

WRF was implemented in INIFAP in order to support the
information needs of forecasts for agricultural regions
•
December 2012:

Experimental stage runnings and validation process

11. Meteorological Forecast
WRF-EMS:
• WRF Environmental Modeling System (EMS), developed by NWS
Science Operations Officer (SOO) Science and Training Resource
Center (STRC)
 http://strc.comet.ucar.edu/index.htm
• Incorporates both dynamical cores on a single forecasting model
(Rozulmalski, 2006)
• The software consists of pre-compiled programs that are easy to
install and run. The WRF EMS contains the full physics options
available for the ARW and NMM cores (Watson, 2007)

12. Meteorological Forecast
Model Configuration:
Simulation Length
Boundry Update Freq



Forecast period of 120 hours
(5 days)
Single domain with a horizontal
spatial resolution of 13 km and a
vertical structure of 35 levels
Initial conditions were obtained from
the Global Forecast System (GFS)
120 Hours
03 Hours
Dynamics
Non-Hydrostatic
Cumulus Scheme
Betts-Miller-Janjic
Microphysics Scheme
Milbrandt-Yau
PBL Scheme
Mellor-Yamada-Janjic
Land Surface Scheme
Noah 4-Layer LSM
Surface Layer Physics
Monin-Obukhov (Janjic)
Long Wave Radiation
RRTM
Short Wave Radiation
Dudhia Scheme

13. Meteorological Forecast
Evaluation:
• Period: July 2012 through
February 2013
• Evaluation points from the
National Agrometeorological
Network
• Selected stations within a
radius of 6 km respect to its
closest point of the grid.
• 386 stations selected to
validate the WRF model
• It was assumed that the grid
points and stations were found
at the same altitude above sea
level

14. Meteorological Forecast
Statistical results of the average of all points
evaluated from July 2012 through February 2013:
Variable
analyzed
Simulation
MAE (mm) ME (mm) RMSE (mm)
day
1
2.26
2
2.32
Precipitation
3
2.44
4
2.47
5
2.61
Simulation
MAE ( C)
day
1
2.81
2
2.75
Temperature
3
2.69
4
2.68
5
2.71
CC
-0.17
-0.11
-0.05
-0.06
0.05
6.25
6.41
6.76
6.82
7.21
0.35
0.34
0.29
0.28
0.23
ME ( C)
RMSE ( C)
CC
1.68
1.61
1.45
1.4
1.35
3.41
3.36
3.31
3.3
3.35
0.76
0.74
0.73
0.72
0.72

15. Meteorological Forecast
Precipitation. Day 1: ME (Mean Error):

16. Meteorological Forecast
Tmin. Day 1: ME:

17. http://clima.inifap.gob.mx

18. Thanks!
corrales.arturo@inifap.gob.mx
gonzalez.miguelangel@inifap.gob.mx

19. References
Rozulmalski, R., 2006: WRF Environmental Modeling System User’s Guide. NOAA/NWS SOO
Science and Training Resource Coordinator Forecast Decision Training Branch, 89 pp.
[Available from COMET/UCAR, P.O. Box 3000, Boulder, CO, 80307-3000]
Watson, L. R. 2007. Weather Research and Forecasting Model Sensitivity Comparisons for Warm
Season Convective Initiation. NASA Contractor Report, NASA/CR-2007–214734, 43 pp
Corrales-Suastegui, A., González-Jasso, L.A., Narváez-Mendoza, M.P., González-González, M.A.,
Osuna-Ceja, E.S., Ruíz-Álvarez, O. y Maciel-Pérez, L.H. 2013. Generación y evaluación
estadística del pronóstico de lluvia a cinco días. Folleto Técnico No. 53. Instituto Nacional
de Investigaciones Forestales, Agrícolas y Pecuarias. Centro de Investigación Regional
Norte Centro, Campo Experimental Pabellón. Pabellón de Arteaga, Ags. México. 23p.
ISBN: 978-607-37-0227-0
Gonzalez-González, M., Ramos-Gonzalez, J.L., Baez-González, A. D. 2009. Validation of a
forecasting method for monthly rainfall in Mexico. Universidad y Ciencia, 25(2):187-192